The Impact of Livelihood Diversification on Rural Household Socio-Economic Conditions: Empirical Evidence from Southern Parts of Khyber Pakhtunkhwa

Abstract

This study examines the impact of livelihood diversification on the socio-economic conditions of rural households in southern Khyber Pakhtunkhwa, specifically in Bannu and Lakki Marwat Districts. For this purpose, a total of 389 sample household were selected through a multistage sampling technique and primary cross-sectional data were randomly collected using structured and administrative questionnaire. Descriptive statistics were used to examine the household socio-economic characteristics, and for a socio-economic dimension indices such as (income, education, health, food security and living standard) a Socio-Economic Composite Index (SECI) was constructed while, multiple linear regression model were used to analyzed the impact of livelihood diversification and related factors on household socio-economic conditions. Descriptive results indicated that the average Livelihood Diversification Index (LDI) was (0.343), with (SD = 0.1881), reflecting variation in income sources. Household heads had an average of (8) years of education, while in averaged households had (10) members, and farm sizes of averaged household was (4) acres. Access to credit facilities, extension services, and climate change adaptation strategies were limited, at (35%), (29%), and (32%), respectively. The multiple linear regression model findings revealed that all explanatory variables had positive and statistically significant impact on rural household socio-economic conditions, as measured by SECI. Specifically, the co-efficient and p-value for livelihood diversification index (LDI) was (β = 0.098, and p-value = 0.007), for household head education was (β = 0.016), and p-value (< 0.001), for family size was (β = 0.004, p = 0.026), and for farm size was (β = 0.005, p = 0.033). Likewise, for farming experience of the respondents was (β = 0.005, p-value = < 0.001), for earning members in household was (β = 0.024, and p = 0.001), for access to credit facilities was (β = 0.039, p = 0.005), while for access to extension services was (β = 0.035, and p = 0.014), and climate change adaptation strategies was (β = 0.040, p = 0.006). This results indicate that enhancements in these indicators significantly improve the socio-economic conditions of rural households. The model explained a strong explanatory power, within R² value of 55.2%, indicating more than half of the variation was explained by the predictors in the SECI. Conversely, the F-statistic = 51.955 and p-value (< 0.001), revealed that the overall model was statistically highly significant, indicating a good model fit. This study recommended that government and development agencies should promote livelihood diversification, human capital, access to institutional support, and climate adaptation strategies is a vital for improving rural household wellbeing.